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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31

Payload Accommodations in NASA's Space Launch System, Block 1 and Beyond

As part of NASA's new deep space exploration system, the Space Launch System (SLS) will provide the United States with guaranteed access to deep space and an unparalleled capability for launching primary and co-manifested payloads beyond Earth's orbit. Planned missions for the new SLS family of vehicles include launching the Orion spacecraft and elements of the new Gateway astronaut-tended outpost to lunar orbit and sending robotic probes deep into the solar system, such as to Jupiter's moon Europa. If mission parameters allow, secondary payloads in 6U, 12U or larger sizes will also have rideshare opportunities, providing CubeSats with access to deep space. The SLS vehicle will evolve into progressively more powerful variants with fairings in several sizes available to meet an array of mission needs. Superior mass, volume and characteristic energy (C3) enable sending larger, heavier payloads to a variety of destinations. Several elements of the Block 1 vehicle for the first mission, Exploration Mission-1 (EM-1) are complete and have been delivered to the Exploration Ground Systems (EGS) Program at Kennedy Space Center (KSC), which has responsibility for integrating and launching the vehicle. Contractors are already at work manufacturing the second Block 1 vehicle and incorporating numerous lessons learned in manufacturing America's first super heavy-lift deep space rocket since the Apollo Program's Saturn V enabled humankind to take a giant leap forward.

Schorr, Andrew A.↗

Expanding Parameter Space to Enable Low-Temperature Synthesis of Crystalline Indium Phosphide Quantum Dots

Established methods to synthesize indium phosphide quantum dots (QDs) require high temperatures (>180 °C) to make high-quality material for optoelectronic applications. Nonpolar solvent environments are overwhelmingly used in InP QD synthesis to reach the necessary high temperatures and for compatibility with the reactive precursors. In this study, we explored InP QD synthesis in polar aprotic solvent environments to dramatically decrease the temperature required for InP crystallization by imparting ionicity to the precursors and stabilizing charged reaction intermediates. A custom air-free 96- well plate setup was employed to identify key factors impacting low-temperature QD formation, including an increased percentage of polar solvent, carboxylic acid choice, and inclusion of polar additives. Guided by these insights, we developed a synthesis of crystalline, green-emitting InP QDs at 60 °C in a toluene-dimethylformamide mixture. Here's, the QDs withstood established Zn 2+ and HF surface treatments, which increased the photoluminescence quantum yield to 25%. Additionally, we demonstrated the rapid synthesis of quasi-wurtzite InP QDs at room temperature in a polar solvent environment using an acid-free indium myristate precursor.

absorption↗

Towards directed energy deposition of metals using polymer-based supports: porosity of 316L stainless steel deposited on carbon-fiber-reinforced ABS

Directed energy deposition (DED) is increasingly valuable to many industries because of its high deposition rates relative to other metal additive manufacturing processes, but the design space of DED is limited. For instance, steep overhangs are difficult or impossible to manufacture. Polymer-based support structures could help address this challenge. The viability of DED on polymer composite substrates has begun to be explored, specifically with 316L stainless steel on carbon-fiber-reinforced ABS substrates. Monolithic metal components can be deposited on the polymer, but it was found that gas release during polymer degradation causes porosity due to gas entrapment in the metal. An interlayer cooling time was introduced to reduce polymer degradation and decrease the porosity due to gas entrapment, but this led to porosity from lack of fusion. The results of this work provide insight into process parameter selection and scan strategy development to enable the use of polymer support structures in blown-powder DED.

Kurfess, Rebecca↗

Co-optimization of fuel properties, combustion system geometry, and injection strategy for conventional diesel fuel

Here, studies have shown that fuel properties can impact an engine’s operation in several ways, including ignition delay, sooting tendency, mixture formation, and combustion temperature. In mixing-controlled compression ignition (MCCI) engines, the fuel system design and piston bowl geometry significantly affect combustion performance and emissions. Based on current information, it is difficult to draw conclusions about fuel property effects and sensitivities. The central fuel hypothesis approach used in the US Department of Energy Co-Optima program has worked well for spark ignition fuels: identifying critical fuel property ranges is sufficient to screen fuel blends that are expected to maximize efficiency and reduce pollutant emissions. However, for MCCI-relevant fuels, the information gained from past studies is not sufficient to build such a merit function or to allow for performing a similar screening of fuel blends. It is hypothesized that a co-optimization of a fuel’s physical and chemical properties, combustion system geometry, and injection strategy could leverage synergies between the effects of the fuel properties and geometries, resulting in improved performance over state-of-the-art. A machine learning–assisted unconstrained global optimization algorithm was used to explore a design space comprising 23 independent variables. The results show that physical property effects were minimal even for large variations in fuel properties, and the only interaction effect that was observed was the effect of varied fuel density parameters on fuel/air mixture formation. Nevertheless, these interactions were not sufficient in magnitude to significantly affect optimization results. Therefore, analysis of the results suggests that fuel physical properties cannot be leveraged in a co-optimization context to increase engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. In this work, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generalized Cycle Benchmarking Algorithm for Characterizing Midcircuit Measurements

Midcircuit measurements (MCMs) are crucial ingredients in the development of fault-tolerant quantum computation. While there have been rapid experimental progresses in realizing MCMs, a systematic method for characterizing noisy MCMs is still under exploration. In this work, we develop a cycle benchmarking (CB)-type algorithm to characterize noisy MCMs. The key idea is to use a joint Fourier transform on the classical and quantum registers and then estimate parameters in the Fourier space, analogous to Pauli fidelities used in CB-type algorithms for characterizing the Pauli-noise channel of Clifford gates. Furthermore, we develop a theory of the noise learnability of MCMs, which determines what information can be learned about the noise model (in the presence of state preparation and terminating measurement noise) and what cannot, which shows that all learnable information can be learned using our algorithm. As an application, we show how to use the learned information to test the independence between measurement noise and state-preparation noise in an MCM. Finally, we conduct numerical simulations to illustrate the practical applicability of the algorithm. Similar to other CB-type algorithms, we expect the algorithm to provide a useful toolkit that is of experimental interest. Published by the American Physical Society 2025

Zhang, Zhihan (ORCID:0009000862907691)↗

The spatial-temporal ambiguity in auroral modeling

The paper examines the time-dependent models of the aurora which show that various ionospheric parameters respond to the onset of auroral ionization with different time histories. A pass of the Atmosphere Explorer C satellite over Poker Flat, Alaska, and ground based photometric and photographic observations have been used to resolve the time-space ambiguity of a specific auroral event. The density of the O(+), NO(+), O2(+), and N2(+) ions, the electron density, and the electron temperature observed at 280 km altitude in a 50 km wide segment of an auroral arc are predicted by the model if particle precipitation into the region commenced about 11 min prior to the overpass.

Rees, M. H.↗

Microbial contamination of spacecraft

Spacecraft and space habitats supporting human exploration contain a diverse population of microorganisms. Microorganisms may threaten human habitation in many ways that directly or indirectly impact the health, safety, or performance of astronauts. The ability to produce and maintain spacecraft and space stations with environments suitable for human habitation has been established over 40 years of human space flight. An extensive database of environmental microbiological parameters has been provided for short-term (< 20 days) space flight by more than 100 missions aboard the Space Shuttle. The NASA Mir Program provided similar data for long-duration missions. Interestingly, the major bacterial and fungal species found in the Space Shuttle are similar to those encountered in the nearly 15-year-old Mir. Lessons learned from both the US and Russian space programs have been incorporated into the habitability plan for the International Space Station. The focus is on preventive measures developed for spacecraft, cargo, and crews. On-orbit regular housekeeping practices complete with visual inspections are essential, along with microbiological monitoring. Risks associated with extended stays on the Moon or a Mars exploration mission will be much greater than previous experiences because of additional unknown variables. The current knowledge base is insufficient for exploration missions, and research is essential to understand the effects of space flight on biological functions and population dynamics of microorganisms in spacecraft. Equally important is a better understanding of the immune response and of human-microorganism-environment interactions during long-term space habitation.

Mir Project↗

A History of Collapse Factor Modeling and Empirical Data for Cryogenic Propellant Tanks

One of the major technical problems associated with cryogenic liquid propellant systems used to supply rocket engines and their subassemblies and components is the phenomenon of propellant tank pressurant and ullage gas collapse. This collapse is mainly caused by heat transfer from ullage gas to tank walls and interfacing propellant, which are both at temperatures well below those of this gas. Mass transfer between ullage gas and cryogenic propellant can also occur and have minor to significant secondary effects that can increase or decrease ullage gas collapse. Pressurant gas is supplied into cryogenic propellant tanks in order to initially pressurize these tanks and then maintain required pressures as propellant is expelled from these tanks. The net effect of pressurant and ullage gas collapse is increased total mass and mass flow rate requirements of pressurant gases. For flight vehicles this leads to significant and undesirable weight penalties. For rocket engine component and subassembly ground test facilities this results in significantly increased facility hardware, construction, and operational costs. "Collapse Factor" is a parameter used to quantify the pressurant and ullage gas collapse. Accurate prediction of collapse factors, through analytical methods and modeling tools, and collection and evaluation of collapse factor data has evolved over the years since the start of space exploration programs in the 1950 s. Through the years, numerous documents have been published to preserve results of studies associated with the collapse factor phenomenon. This paper presents a summary and selected details of prior literature that document the aforementioned studies. Additionally other literature that present studies and results of heat and mass transfer processes, related to or providing important insights or analytical methods for the studies of collapse factor, are presented.

deQuay, Laurence↗

Microbial Contamination in the Spacecraft

Spacecraft and space habitats supporting human exploration contain a diverse population of microorganisms. Microorganisms may threaten human habitation in many ways that directly or indirectly impact the health, safety, or performance of astronauts. The ability to produce and maintain spacecraft and space stations with environments suitable for human habitation has been established over 40 years of human spaceflight. An extensive database of environmental microbiological parameters has been provided for short-term (< 20 days) spaceflight by more than 100 missions aboard the Space Shuttle. The NASA Mir Program provided similar data for long-duration missions. Interestingly, the major bacterial and fungal species found in the Space Shuttle are similar to those encountered in the nearly 15-year-old Mir. Lessons learned from both the US and Russian space programs have been incorporated into the habitability plan for the International Space Station. The focus is on preventive measures developed for spacecraft, cargo, and crews. On-orbit regular housekeeping practices complete with visual inspections are essential, along with microbiological monitoring. Risks associated with extended stays on the Moon or a Mars exploration mission will be much greater than previous experiences because of additional unknown variables. The current knowledge base is insufficient for exploration missions, and research is essential to understand the effects of spaceflight on biological functions and population dynamics of microorganisms in spacecraft.

Pierson, Duane L.↗

Parametric Testing of Launch Vehicle FDDR Models

For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.

Schumann, Johann↗

Exploring Climate With Obliquity in A Variable-Eccentricity Earth-Like World

Exploring planetary systems similar to our solar system can provide a means to explore a large range of possibly temperate climates on Earth-like worlds. Rather than run hundreds of simulations with different eccentricities at fixed obliquities, our variable-eccentricity approach provides a means to cover an incredibly large parameter space. Herein Jupiter's orbital radius is moved substantially inward in two different scenarios, causing a forcing on Earth's eccentricity. In one case, the eccentricity of Earth varies from 0 to 0.27 over ∼7000 yr for three different fixed obliquities (0°, 23°, and 45°). In another case, the eccentricity varies from 0 to 0.53 over ∼9400 yr in a single case with zero obliquity. In all cases, we find that the climate remains stable, but regional habitability changes through time in unique ways. At the same time, the moist greenhouse state is approached but only when at the highest eccentricities.

Exoplanet astronomy↗

Modelling and Analysis of a Regenerative Fuel Cell Propulsion System for a High Altitude Long Endurance UAV

In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked

Simpson, Mike B.↗

Multidimensional synthetic estimation filter

The synthetic estimation filter (SEF) crafts an affine variation into its response to a changing parameter (e.g. scale or rotation). Sets of such filters are used in an estimation correlator to reduce the number of filters required for a given tracking accuracy. By overspecifying the system (one more SEF than parameters to be tracked), the ratio of correlation responses between filters forms a robust estimator into the spanned domain of the parameters. Previous results dealt with a laboratory correlator which could track a single parameter. This paper explores the SEF and the estimator's extension to more dimensions. A 2D example is given in which a reduction of filters from 25 to 3 is demonstrated to span a 4-degree square portion of pose space.

Monroe, Stanley E., Jr.↗

Performance projections for laser beam power to space

We examine the requirements placed on an adaptive-optics system used to compensate atmospheric effects in propagating high-power lasers from ground to space. The particular application involves energy transfer from a ground station to a satellite. Our analysis explores performance associated with various beacon configurations, including satellite-based beacons, beacons in the lead-ahead direction, and synthetic beacons. Other system parameters are adjusted as well, including number of actuators in the deformable mirror and bandwidth of the servo system. We show that with an optimized system design it is possible to achieve collection efficiencies of 10-50 percent over zenith angles as great as 70 deg.

Greenwood, Darryl P.↗

Trajectory Design Considerations for Exploration Mission 1

Exploration Mission 1 (EM-1) will be the first mission to send an uncrewed Orion vehicle to cislunar space in 2018, targeted to a Distant Retrograde Orbit (DRO). Analysis of EM-1 DRO mission opportunities in 2018 help characterize mission parameters that are of interest to other subsystems (e.g., power, thermal, communications, flight operations, etc). Subsystems request mission design trades which include: landing lighting, addition of an Orion main engine checkout burn, and use of auxiliary thruster only cases. This paper examines the evolving trade studies that incorporate subsystem feedback and demonstrate the feasibility of these constrained mission trajectory designs and contingencies.

Dawn, Timothy F.↗

Methods for System-Level Multidisciplinary Uncertainty Analysis of Low-Boom Flight Vehicles

Current research supporting NASA’s Commercial Supersonic Technology project is focused on the efficient prediction of uncertainty in sonic boom loudness generated by low-boom aircraft concepts. This paper focuses on research incorporating aircraft trim and aerostructural analysis into a multidisciplinary system-level uncertainty analysis. This enables the modeling of a steady-state representation of a point in the uncertainty space, simulating the vehicle as it would be flown. This approach also enables multiple uncertain parameters defining the configuration of the vehicle to be reduced to three: Mach number, altitude, and aircraft weight. To demonstrate this methodology, a case study exploring a conceptual low-boom supersonic aircraft is performed. Two different approaches are used to model the interactions between nearfield pressure signature analysis and sonic boom propagation, and their performance is evaluated in terms of accuracy and computational expense. One method uses a set of local surrogate models to generate a large number of nearfield signatures and perform Monte Carlo analysis. This method is found to produce, at a lower expense, uncertainty metrics that are comparable to the second method, in which uncertainty metrics are computed based on loudness metric values obtained directly from simulated nearfield signatures.

UQ↗

Method for System-Level Multidisciplinary Uncertainty Analysis of Low-Boom Flight Vehicles

Current research supporting NASA’s Commercial Supersonic Technology project is focused on the efficient prediction of uncertainty in sonic boom loudness generated by low-boom aircraft concepts. This paper focuses on research incorporating aircraft trim and aerostructural analysis into a multidisciplinary system-level uncertainty analysis. This enables the modeling of a steady-state representation of a point in the uncertainty space, simulating the vehicle as it would be flown. This approach also enables multiple uncertain parameters defining the configuration of the vehicle to be reduced to three: Mach number, altitude, and aircraft weight. To demonstrate this methodology, a case study exploring a conceptual low-boom supersonic aircraft is performed. Two different approaches are used to model the interactions between nearfield pressure signature analysis and sonic boom propagation, and their performance is evaluated in terms of accuracy and computational expense. One method uses a set of local surrogate models to generate a large number of nearfield signatures and perform Monte Carlo analysis. This method is found to produce, at a lower expense, uncertainty metrics that are comparable to the second method, in which uncertainty metrics are computed based on loudness metric values obtained directly from simulated nearfield signatures.

Supersonics↗